2013 NUE Conference Des Moines, Iowa August 5-7 Jacob T. Bushong.

DEVELOPMENT OF AN IN-SEASON ESTIMATE OF YIELD POTENTIAL

UTILIZING SOIL MOISTURE DATA FOR WINTER WHEAT

2013 NUE ConferenceDes Moines, Iowa

August 5-7

Jacob T. Bushong

Current OSU winter wheat midseason N rate recommendations are determined using:

◦ Grain Yield Potential

◦ Response index (RI), N-Rich strip and the farmer practice

◦ Assumed maximum grain yield for the region

◦ Economic factors (grain price & fertilizer price)

Introduction

Farmer Practice

N-Rich Strip

Based upon NDVI and GDD In-season estimate of yield (INSEY)=NDVI/GDD

Grain Yield Potential

Aids in stand establishment and early vegetative growth

Increases nutrient uptake of mobile nutrients

Yields can be maximized if consistent available water is present throughout the growing season

Soil Moisture Impact on Grain Yield Potential

To improve the current method for estimating in-season grain yield potential by utilizing soil moisture data.

Objective

Photo courtesy of Oklahoma State University

+ =

Oklahoma Mesonet◦ Collaboration with Oklahoma State & University of Oklahoma◦ 120 automated weather monitoring stations statewide◦ Measures air temperature, wind speed, soil temperature,

soil moisture◦ Soil moisture data, since 1996

Weather Monitoring

Soil Moisture◦ Heat dissipation sensors◦ Depths of 5, 25, 60, 75 cm◦ Data reported as

Fractional Water Index (FWI) Range from 0.00 to 1.00

Soil Temperature◦ Recorded at 1.5 m above

the surface

Soil Moisture & Temperature

Downloaded from website◦ www.mesonet.org

Average daily values

SQL queries designed to retrieve desired data

Data Acquisition and Manipulation

Normalized Difference Vegetation Index (NDVI)

Growing Degree Days (GDD’s)

Soil Moisture Factor (SMF)

Model Inputs

Collected with Trimble Greenseeker Optical Sensor

Normalized Difference Vegetation Index (NDVI)

NDVIRED =ρ780 - ρ670

ρ780 +ρ670

Current: Days from planting to sensing where the average daily temperature > 4.4 °C

Proposed: Days from planting to sensing where the average daily temperature > 4.4 °C and FWI > 0.30

Growing Degree Days (GDD’s)

Stillwater, OK (2012-13)

9/30/2012 11/19/2012 1/8/2013 2/27/2013 4/18/2013 6/7/20130.00

0.10

0.20

0.30

0.40

0.50

0.00

0.20

0.40

0.60

0.80

1.00

Irrigated Non-Irrigated

FWI

ND

VI FW

I

GDD 47 77 98 136 180

Data sources: USGS Earth Explorer and Mesonet.org

Proportion of 0-80cm PAW at sensing to the daily water use (ET) of the growing crop from sensing to harvest◦ Assumed harvest date of June 10◦ Assumed daily water use 5 mm day-1

FWI index converted to PAW utilizing soil water content values (PWP, FC, SAT) from USDA-NRCS soil survey

Value cannot exceed 1.0

Soil Moisture Factor (SMF)

Lahoma: Grant silt loam (fine-silty, mixed, superactive, thermic Udic Argiustolls) Stillwater: Kirkland silt loam (fine, mixed, superactive, thermic Udertic Paleustolls) Perkins: Konawa fine sandy loam (fine-loamy, mixed, active, thermic Ultic Haplustalfs)

Model Calibration Sites

Data collected from 2003 to 2011 22 total site-years of data Plots had a wide range of pre-plant N

rates Data collected over a range of growth

stages (Feekes 3 to 10)

Model Validation Sites Lahoma: Grant silt loam (fine-silty, mixed, superactive, thermic Udic Argiustolls) Stillwater: Kirkland silt loam (fine, mixed, superactive, thermic Udertic Paleustolls) Perkins: Konawa fine sandy loam (fine-loamy, mixed, active, thermic Ultic Haplustalfs) Hennessey: Bethany silt loam (fine, mixed, superactive, thermic Pachic Paluestolls) LCB: Port silt loam (fine-silty, mixed, superactive, thermic Cumulic Haplustolls) LCB: Konawa fine sandy loam (fine-loamy, mixed, active, thermic Ultic Haplustalfs)

Data collected from 2012 and 2013 11 total site-years of data Plots had a wide range of pre-plant N

rates Data collected over a range of growth

stages (Feekes 3 to 10)

Stepwise regression was utilized◦ Maximize the adjusted R2

Three models developed◦ All Calibration Sites (Lahoma, Stillwater, Perkins)◦ Loamy Calibration Sites (Lahoma, Stillwater)◦ Coarse Calibration Site (Perkins)

Model Development

All Sites Loamy Sites Coarse Sites

Parameter Est. Pr > |t| Est. Pr > |t| Est. Pr > |t|

Intercept 8.32 --- 9.62 --- 4.68 ---

GDD -0.09 <0.0001 -0.08 0.0320 -0.06 0.1261

SMF -10.66 <0.0001 -13.82 <0.0001 -5.03 0.2157

NDVI -15.68 <0.0001 -17.17 0.0005 -13.19 0.0356

GDD*SMF 0.11 <0.0001 0.11 0.0029 0.05 0.2408

GDD*NDVI 0.22 <0.0001 0.18 0.0051 0.23 0.0014

NDVI*SMF 25.80 <0.0001 31.44 <0.0001 16.51 0.0250

NDVI*GDD*SMF -0.28 <0.0001 -0.27 <0.0001 -0.22 0.0064

Model Parameters Estimates

ValidationResults

2012 FK 4

2012 FK 5

2012 FK 6

2012 FK 7

2012 FK 10

2012 All

2013 FK 4

2013 FK 5

2013 FK 7

2013 All

All0.00

0.20

0.40

0.60

0.80

1.00Current INSEY All Sites New INSEY Loamy Sites New INSEY

Lahoma (Grant)R

2

2012 FK 4

2012 FK 5

2012 FK 6

2012 FK 8

2012 FK 10

2012 All

2013 FK 7

All0.00

0.20

0.40

0.60

0.80

1.00Current INSEY All Sites New INSEY Loamy Sites New INSEY

Stillwater (Kirkland)R

2

2012 FK 4

2012 FK 5

2012 FK 6

2012 FK 7

2012 All

2013 FK 3

2013 FK 4

2013 FK 5

2013 FK 6

2013 FK 7

2013 FK 10

2013 All

All0.00

0.20

0.40

0.60

0.80

1.00Current INSEY All Sites New INSEY Loamy Sites New INSEY

Hennessey (Bethany)R

2

2012 FK

4

2012 FK

4

2012 FK

5

2012 FK

8

2012 All

2013 FK

3

2013 FK

7

2013 FK

9

2013 All

All0.00

0.20

0.40

0.60

0.80

1.00Current INSEY All Sites New INSEY Loamy Sites New INSEY

Lake Carl Blackwell (Port)R

2

FK 3 FK 4 FK 5 FK 6 FK 7 FK 8 FK 9 FK 10 All0.00

0.20

0.40

0.60

0.80

1.00Current INSEY All Sites New INSEY Loamy Sites New INSEY

All Loamy SitesR

2

2012 FK 4

2012 FK 5

2012 FK 6

2012 FK 8

2012 FK 10

2012 All

2013 FK 3

2013 FK 4

2013 FK 5

2013 FK 6

2013 FK 7

2013 FK 10

2013 All

All0.00

0.20

0.40

0.60

0.80

1.00Current INSEY All Sites New INSEY Coarse Sites New INSEY

Perkins (Konawa)R

2

2013 FK 3 2013 FK 4 2013 FK 5 2013 FK 7 2013 FK 10 2013 All0.00

0.20

0.40

0.60

0.80

1.00Current INSEY All Sites New INSEY Coarse Sites New INSEY

Lake Carl Blackwell (Konawa)

R2

FK 3 FK 4 FK 5 FK 6 FK 7 FK 8 FK 10 All0.00

0.20

0.40

0.60

0.80

1.00 Current INSEY All Sites New INSEY Coarse Sites New INSEY

All Coarse SitesR

2

FK 3 FK 4 FK 5 FK 6 FK 7 FK 8 FK 9 FK 10 All0.00

0.20

0.40

0.60

0.80

1.00Current INSEY All Sites New INSEY

All SitesR

2

0 1 2 3 4 5 60

1

2

3

4

5

6

f(x) = 1.00046275471595 x + 0.254190036879882R² = 0.494351668999938

Act

ual Yi

eld

(M

g/h

a)

Predicted Yield (Mg/ha)0 1 2 3 4 5 6

0

1

2

3

4

5

6f(x) = 1.28260846253859 x + 0.294942703327537R² = 0.401827619304635

Predicted Yield (Mg/ha)

Act

ual Yi

eld

(M

g/h

a)

All SitesNew INSEY Current INSEY

RMSE = 0.92 RMSE = 0.95

XX

Soil moisture at the time of sensing had a significant effect on final wheat grain yield for all locations

Models that included soil moisture parameters typically outperformed current models at most locations

One model developed from loamy and coarse textures sites is sufficient to use compared to having different models based on soil type.

Conclusions

Investigate the GDD adjustment for soil moisture◦ What depth?◦ Soil moisture threshold?

Evaluate which estimate of grain yield provides the most accurate mid-season N rate recommendation

Evaluate if Vertisol soils can use the new model or if they need their own model

Next Steps

Questions?